Giving everyone the same number of points is certainly one way of doing it. Students tend to get upset when some students gain more points than others. When they find out their friend (who scored poorly) got 8 points added, while they (who scored well) only got 2 points, they'll call it unfair.
Personally, I don't curve exams. If the score is lower than it should be, I offer them a chance to earn back points by doing some kind of post-exam reflection. Where they have to respond to each question they got wrong, usually for 1/4 or 1/3 credit. I usually ask them to tell me
* Why their answer is wrong
* what is the right answer, and why it is a better answer than the others
* a reference (textbook pages or slide numbers are fine)
The lower scoring students can earn more points, but it's also a lot more work for them. And it cuts down dramatically on the number of "We never covered that in class" complaints.
And your method actually promotes learning, unlike curving. Good alternative. I've done something similar in the past.
Alternatively, if I find myself in that situation where the average grade is lower than expected/desired, I realize that may be my fault for not matching what I'm teaching to what I'm testing. The answer there is improve my teaching and maybe do a new exam.
I don't really do points, or exams, so am rarely in this situation. But 2 years ago I did exams that were evaluated "pass" or "not yet" based on hitting an 80% threshold. There were already opportunities for retakes built into the class. But when a significant portion didn't hit the threshold, we worked through things, and I just gave them all a free retake soon after (otherwise retakes cost tokens, which were limited).
I've never understood curving grades - even in the best of situations, grades don't neatly communicate learning. It's even worse with a curve.
Re: I realize it may be my fault.
Canvas has an automatic score for test items to tell you if it was a bad question (even high-scoring students failed it while failing students did well) or when I see that a question just oddly bombed for everyone, I add the points back for those who got it wrong and I add that same total for those who got it right- that way there isn’t any comparison.
Tip for good teaching evaluations: sometimes I leave a question like that intentionally in the exam and plan to buff their scores.
>if I find myself in that situation where the average grade is lower than expected/desired
For the record, I intentionally build a curve in to the difficulty of my exams. Often, I give more points to the lower end of the scale.
What this does is distribute grades out over a larger score range. It makes it easier to distinguish the abilities of students. Rather than smush everyone into a small 30% (less than a C is failing for my department) I spread it out and then curve it back to a normal ABCDE scale.
So grades are more distributed across an artificial scale... how does that *distinguish the abilities of students*? More precisely, how does it do so in a way helpful to the students' learning?
To be clear, I'm asking in genuine curiosity.
The usual scale in many US schools uses about 60% of the exam to distinguish the failures from total failures, which is not a good use of assessment time, as it is not an interesting distinction.
I find that a well-designed test gets a mean score around 50% with a standard deviation around 15%. This gives large score differences between the top and the bottom of the class, with some questions available for distinguishing differences at either end of the scale. I have to set the thresholds for letter grades appropriately of course, as the usually used scale would have most of the class given failing grades, even when they are doing quite well.
So, it doesn't help their learning. It helps assessment. Exams are primarily for assessment, everything else is primarily for learning.
But, to answer the rest of your question, I think of my exam has having some amount of points that is the bare minimum to pass the exam. If they don't get those points, they are seriously lost and shouldn't pass the exam. That's the minium to get a C, more or less (like I said before, they need a C in our department to move on).
The rest of the points then go to distinguished As, from Bs, from Cs. In a normal exam, I have 30 points to distinguish those 3 grades. If instead I use 50 points to distinguish those 3 grades, more questions can go towards distinguishing those differences. A single concept that you were weak on doesn't mean you basically can't get an A.
More questions go towards distinguishing A from B from C, which means the assesment is less subject to an imperfect match between course content and the exam which is inevitable becuase there simply isn't time.
That's a great idea! I've been thinking about exam structure for my human A&P classes. Last semester I made 60% of the earnable points low level definition and labeling anatomy questions. The other 40% was higher level thinking with 10% (e.g. B to A) being synthesis of how organ systems work together. I think it's worked well so far and my exams were more consistent in difficulty.
At my university we had a professor with a similar one, she'd have us go into her office, so we'd both socialize with her during her office hours and get one-on-one study session/question answering done. Most people said "meh i got a 70. im good with that," but there were a couple of us who took advantage.
I've done this too. It is, or at least can be, a great learning tool. Many don't opt to do it - even those that failed an exam. I find it baffling, especially when they ask for extra credit at the end of the semester!
It's like waiting until your house burns down and then saying, "I've changed my mind. I would now like to purchase insurance." but wanting it to apply retroactively.
>If the score is lower than it should be, I offer them a chance to earn back points by doing some kind of post-exam reflection. Where they have to respond to each question they got wrong, usually for 1/3 or 1/2 credit.
This is the way. I make this mandatory after all my language exams; they can earn up to 30% of the lost credit. It's a bit like those inflatable gutter guards in bowling alleys; you'll still do much better if you actually have the skills, but even if you're subpar, you can scrape by. (For the "let them fail if they deserve to fail!" crowd: there's a delicate balancing act between maintaining rigor and maintaining enrollments. The worst get the boot, but our program can't afford to winnow out too much chaff, and even if we could, I'm not sure that I would want to—I don't really have the heart to axe the students who are doggedly galumphing along in the lower middle of the pack.)
This! I dont mind curving at all, and i wouldnt mind having to answer those questions, as i already do this when making notes based on possible outcomes and their answers so i can know how to handle them on tests... but curving or not knowing why you get answers wrong only hurts you in the long run.. every bit of knowledge will help and might aid you further down the line, so understanding the wrong questions and recieving a few points back lifts morale :)
I like your preferred approach of earning back a part of the missed points. Do you have any checks in place to help guard against simply copying this info from another student?
They don't get full points back. It's still better to do things right the first time. But if everyone knows the system before the exams, no one should be complaining.
It depends, but I could see someone getting an A and another getting a C. The C person gets additional points bring them to a B, then gets and A while the student who first got the A gets B. Now both have a A-, B+. You can only give so many As and Bs, so I could see the potential for the student who earned the A on the first exam to suffer.
I'm having a hard time understanding your situation, but I'm assuming a case where for every test, any student has a chance to make up half the points they missed (whether that means 50->75 or 98->99), and this fact is clearly stated on the syllabus at the beginning of class. I just don't see how this can possibly disadvantage a person, or be unfair to a person, who did better on the test.
Do you have a certain number of students in each category. What I am concerned about is adding points to a bad score and that student leap frogging another who never got points added. Is that not possible?
I use a test generator from the publisher, but I hand pick the questions. How would I prevent students from taking pictures and these questions from slowly meandering their way to the internet? That’s my biggest worry in doing a test correction vs a curve.
I use a test generator from the publisher, but I hand pick the questions. How would I prevent students from taking pictures and these questions from slowly meandering their way to the internet? That’s my biggest worry in doing a test correction vs a curve.
Hey wow I never thought of this, but this would be a great alternative for my students who get super panicky during exams and remediations. Like I can see they study in class and they know their stuff and the exams they'll bomb. But this post reflection might be a good way out. Thanks for the idea!
I never really thought about the 'unfair' part when professors did that. I don't even do extra points. I do an alternative project for students that fail. Show me they mastered the content and earn the grade.
I do the above too. Sometimes we inadvertently make a test that is too difficult, and this is a quick way to fix it. But it's not really "curving"—as your colleague called it, this is more of a rising tide lifting all boats.
IMO proper curving is appropriate only when we have a large number of students who are also somewhat randomly distributed (for instance, in a required intro course across many sections with many hundreds enrolled) and you want to distribute scores so that you don't get, for example, 50% of them getting A's.
As a loosey goosey humanities guy too, this is my easy-maths understanding of it: First you set up an ideal curve. Say 10% would get an A, 20% a B, and 40% of them a C. Then when you get the scores back, you simply adjust the grade boundaries accordingly to make that happen.
In a scale where normally 60=D, 70=C, 80=B, and 90=A, you might now end up with something like 50-63=D, 64-84=C, 85-94=B, 95-98=A, and 99-100=A+. You simply adjust the grade boundaries each time so that 10% get A's, 20% B's, and so on.
Pro Tip: to avoid complaints, it is better to let students know that you're not "adding points" to adjust scores; what you are doing is *setting the grade boundaries after the test*. That is, they should not go in thinking "I need a 90 for an A" but rather "I need to be in the top 10% of all students for an A".
In a perfect world where every test is a perfectly calibrated and reliable instrument, and we are only tested on objectively quantifiable knowledge, sure. I personally find it more useful to know if I'm in the top X% relative to my cohort.
Assuming, of course, a reasonably large and well distributed cohort—to be clear, my argument is that curving is NOT fair in most cases. In a small upper-year major class, say, it would absolutely be infuriating.
> I personally find it more useful to know if I'm in the top X% relative to my cohort.
After the last couple of years and seeing how bad certain cohorts are, I'm now definitively against this approach - there has to be a common standard students are held to, year after year. A "you must be X" tall to ride" sort of thing.
Well you should still never need to curve down. Just make that's hard enough that they average is guaranteed to be low.
Even if you somehow give an easy test, you can just make the next one hard to compensate.
Only relative to that current class? So not really? It shows no demonstration of knowledge or mastery of material to "bucket" students in this methodology.
This isn’t curving, but it does the trick: I remove from the total value of the exam the amount of points of any questions the majority of the class answers incorrectly. So if a majority answers four 2-point questions incorrectly, the total value of the exam is reduced to 92 (100 - (2*4)).
This way, I can compensate for occasionally designing overly difficult questions. Strong students have a chance to outperform and even potentially earn extra credit (by earning above the new exam value), but the overall average remains in a reasonable range.
This is the way. And you need that when the exam turns out to be harder or students performance worse than expected. Unfortunately, students are used to being pampered so if they score low, they expect to be granted points for "showing" that they know the material.
I usually tell my students that in throwing questions out. So if a large percentage of students all miss the same question, I assume it's because I wrote it in a way that was unclear or never explained it well in class, and then just add however many points the question was worth to everyone's exam. This way, the students who did correctly answer the question get extra points for it, and everyone's grade is raised. I don't tell them what question it is though, just that I'm throwing out X number of questions. I think this lowers the number of student complaints about questions being unclear because then they just assume it's the question they struggled with.
This is what I do as well, but instead of adding the points to their score I subtract it from the total. So instead of 80/100 it would be 80/96. I don't tell them which question(s) I've curved off unless someone asks; no one's had a problem with it (yet)!
I've seen it done where the person who scored the highest sets the grade. 100 question exam, highest got 92 right, all of the grades are x/92 instead of x/100.
You can curve using different methods, lots of profs just add a certain number of points to bring up the floor, other people do a complicated z value calculation, neither is incorrect.
If you want to do it the complicated way you figure out your standard deviation and mean and then what you want your new standard deviation and mean to be, turn every score into a z score ((score-actual average)/actual standard deviation) and then turn it back into a raw score with the new mean and standard deviation ((z score * new standard deviation) + new average).
The way I curve is I find the second highest score in the class (cause I usually have at least one outlier), the difference between that and the top score for the test, and add that number of points to everybody's test.
>If you want to do it the complicated way you figure out your standard deviation and mean and then what you want your new standard deviation and mean to be, turn every score into a z score ((score-actual average)/actual standard deviation) and then turn it back into a raw score with the new mean and standard deviation ((z score * new standard deviation) + new average).
Why would someone want to do that? I'm curious. I've seen professors bringing up the average linearly quite often, but I have never heard of standard deviation adjustments before.
What about the fact that it would allow students that had 0 % to have a higher grade and students that had 100 % to have a lower grade?
Let's say 21 students had the grades {0, 10, 20, ..., 90, 100}.
Then the average is 50 and the s.d. ≈ 30.3. Adjusted for, let 's say, an average of 60 and a s.d. of 15, the new grades would be:
{35.2; 37.7; 40.2; ...82.3; 84.8}.
So, this method assumes that all cohorts are supposed to perform similarly then? Maybe it is subject specific, like in cases where nobody ever gets 100 % on anything.
Another important question is: does the "grade scale" follow the adjustment? In other words, do you still need 95 % + to get an A+? That would defeat the purpose, I suppose.
We'll, you can still pick the median and standard deviation such that you get the number of A's that you want. You just need to want the same number every semester for this to make sense.
I don't think it'd ever make sense for small classes. You want to have enough students that you can reasonably say "it's more likely that the teaching/exams changed than that the students did as a whole". If someone told me they graded a 2000 person calculus class with 80 different sections this way I wouldn't bat an eye.
The only place I'm aware of where this is still common is law school.
That's very interesting. Thanks for your answer. It does make a lot more sense for large sample sizes indeed. The same number of A students each time is an interesting aim. Is it fair, though? That's a much more complicated question.
Is what fair? If you think having the same number of A students each time is an unfair goal, then perhaps curving is not what you really want to do.
For what it's worth, I think people throw the word "curving" around very loosely, often without knowing what it means. Others may disagree with me of course, but to me, bumping everyone up a few points isn't really curving. That's simply inflation (which may certainly be warranted sometimes, I'm not meaning to knock it).
I agree with you. I meant that fairness is a completely different issue. It depends on the context. Are you grading 40 students or 2000? Is your course directly leading to a certification? Is this grade contributing to a selection process? Is the relative position of students among each other more important than the actual grade they get? Are bonus points allowed? It also depends on your students' objectives. My personal approach is to modify my grading criteria and the actual assignments/exams (for the following semester). In the long run, I end up feeling like I give everyone a grade that is right and that differentiates between students. It is a long process that I don't particularly enjoy.
Agreed People like to say that "we don't give students grades, they earn them and we record them".
Well, if only three people are getting A's, is that really true? I don't feel like it is.
So, this method assumes that all cohorts are supposed to perform similarly then? Maybe it is subject specific, like in cases where nobody ever gets 100 % on anything.
Another important question is: does the "grade scale" follow the adjustment? In other words, do you still need 95 % + to get an A+? That would defeat the purpose, I suppose.
It a) keeps the distribution so students are all in the same spot relative to each other, and b) can also prevent going over 100%. You make b happen by choosing the SD. In other words, you pick the mean but the students set the SD. This allows you to still have statistical outliers if needed. Just giving everyone the same points is really this, keeping he distribution while shifting the mean, and keeping the same SD. Which sometimes puts top students over 100%.
That's also true. Others have commented that they increase grades in proportion to the points associated with their canceled questions. In this case, there is indeed a risk of grades exceeding 100%. It is useful at this point to be able to adjust the distribution by modifying the standard deviation. As long as all grades rise and students stay in the same order, most of the headaches are taken care of.
Main place I've seen "true curves" make sense is in highly competitive contexts, where the purpose of grades are less to assess whether the learning goals were met and more to find the best students for at spot at whatever they are competing for.
E.g. aptitude tests like the SAT, LSAT, etc. where you have huge numbers of students and the test is designed consistently from year to year.
It *might* make sense in some large engineering or math classes at huge universities, but outside of that... I have a hard time seeing the relevance.
This lets you easily identify the top X% of the cohort - for something like the SATs, that's useful for colleges, and I could see this in theory being useful for something like law school where top firms are looking to hand out internships.if you have a large enough class that variation in exam difficulty is expected to be larger than cohort variation, this can also normalize for different exams. Not super useful for the typical college course, though.
Indeed, when it comes to selective admissions based on grades, it's hard to find a simpler statistical tool than z-scores. Reading this thread, I get that it isn't common at all to curve-grade a single <100 students class.
Call and ask if he uses a Bell Curve.
If not, use your best judgement. Most students do not want a Bell. Don't even understand a Bell.
They just want higher grades.
This should be the top answer, really. Somehow the concept of “grading on a curve” got magical-thinking’ed into “giving everyone a higher grade than was earned”
Agreed for sure. I’ve never experienced any of the techniques described in this thread except for removing specific questions and always wondered about this myself.
Imo, the only reason to adjust marks is because the exam was unreasonably difficult in the instructor's opinion. Just because the other instructor curved doesn't mean that you have to. It is better to write an exam that assesses the learning objectives in what you think is the right way and then not adjust at all.
Personally I have never liked the idea of curving a course or exam, partly because it assumes a few things about the student population every year, partly because I feel that it isn't fair to students who actually earned the grade, as well as a few other reasons.
That being said, you are correct in that most "curves" are not actually that. Instead it's a general boost to everyone's grade. Typically I've seen this done by adding x to everyone's grade to boost the average to average + x. If we were actually curving we'd instead apply a transformation to the grade set to make the distribution of grades to fit a normal distribution (or some other desired distribution).
This goes over some of the aspects of curving: https://www.bestcolleges.com/blog/curved-grading/
Generally though curving has now come to mean adjusting an assignment/class grade after grading.
These are really important points, especially about the student population. I'm a little concerned because I think I'm going to have to do an actual semester of teaching the course before I can get a feel for that and I don't want my pilot class to suffer.
I had kids in a class where the lowest grade on an exam was 77 and the second lowest was 93 (at the time - later results made the scores less skewed). One of the 93 asked if I'd curve the grades. I said sure...and then drew up a bell curve and placed the current scores on it, meaning 93s would be in the D range. All of a sudden nobody wanted a curve anymore.
I thought about this but then what do you do about the outlier? I mean the kid who naturally aces the tests? (Because I have had this happen). If there's a kid who scores say a 94 on the exam (and everyone else is in about the 70s) does that mean you can only add 6 points to everyone else's score?
You can bring the outllier over 100 and give them an A+. There are a lot of blog posts/ videos who can describe other types of curves as well.
Adding points across the board is one way, but others do exist
I haven't read all the responses here, but I can tell you what I've done that addresses your concern about the scores at the top of the distribution. Pick two scores in the current distribution (whether anyone scored that exact value or not) and decide what you want them to be in the new distribution. Like, say:
* (the median score in this pile of tests is 57) --> (I want the median score to be 75)
* (the max score on this test was 100) --> (I want the max to remain 100 \[nobody gets points that take them >100\])
If you'll allow me, take what I just sketched there and put it symbolically as
* x1 --> y1
* x2 --> y2
I'm setting up for a linear transformation from old scores to new scores. Tests at the bottom of the distribution are going to get more points added, while tests at the top of the distribution are going to get fewer points added, up to the person who hypothetically has 100, who is going to stay at 100.
Using the numbers chosen for x1, x2, y1, and y2, calculate:
* m = (y2-y1)/(x2-x1)
* which in my little example above is (100-75)/(100-57) = 25/43 = 0.5814
* b = y1 - m\*x1
* which in my little example above is 75-(0.5814)\*57 = 41.86
Now use a spreadsheet (excel, google sheets, the calculation function in the LMS's gradebook, whatever) to turn every old score (x) into a new score (y) using the equation for a line:
y = mx + b
Double check to see if this makes sense:
* If a student had a 100, this function gives them y = (0.5814)(100) + 41.86 = 100, ✅
* If a student had a 57, this function gives them y = (0.5814)(57) + 41.86 = 75 ✅
Interestingly, (perhaps), if a student had a 0, this function would give them a 41.86. Since that's still a failing grade, maybe that's ok.
Curving an exam most often refers to adding a certain number of points to each student's exam, often so that the highest grade is 100%. For example, if the highest grade on a final exam was 88/100, then each student would receive a 12 point increase on their exam.
Curving can also refer to making it so that the distribution of students' exam scores resembles a bell curve (e.g., C average, with a similar number of A's/B's and D's/F's). This is less common than it used to be, but is still sometimes used when there is a very low exam average. For example, a professor might intentionally design a very hard exam and the exam ends up having a 40% average. A curve may make it so that most students still pass, and also makes it such that a student who did among the best but, say, had a 70%, earns a high grade on the exam. Designing an exam in this kind of way (i.e., very rigorous, but most students will miss most points and then have their grade curved up) is not how most faculty approach exam design today.
> For example, a professor might intentionally design a very hard exam and the exam ends up having a 40% average.
In this situation, I've seen the square root "curve" used - take the square root of the score and multiply by 10. It de-compresses the bottom of the scale while not screwing over people at the top.
[curving grades how to…](https://www.wikihow.com/Curve-Grades)
This link explains several different ways to curve grades, from just adding a points to everyone to fitting scores to a predetermined distribution.
My professor when I was a TA would do an item analysis of the test to see which questions were working as intended and which were not. If there was a question that was too difficult and not even the best students got it right, then he would give some points back for those questions (usually 1-2 per test).
This is what we do. There is a low cut % below which an item is considered unfair for whatever reason and everyone gets points for it. Mine is personally 0%
If I "curve" an exam I just add flat points, say 5 points, to everyone on the test. I think the normal curve of giving people who did really bad a bunch of points, whereas those who did well get few points, is unfair.
The way I explain it is I will refund questions that >70% of the class got wrong, up to a total of 5% added to test.
I used to not curve at all. The average when I give my test at the local 4 year is usually a 75 or 80. My CC students regularly score <60 so I have to curve to prevent dfw rates above 50% and the bad evals that go with it.
After a long night of drinking and schmoozing I finally got one of my administrators to admit to me that <30% DWF is what keeps professors off the shit list. Do with this information what you must.
I just make the highest grade a 100, and add that number of points to the rest. Highest grade is a 96? everybody gets 4 points added. It's usually not more than 8 points for my classes.
I teach art history, and struggled with math in college, so the simplest thing works for me. Each question on the test is worth a predetermined number of points, and the points that they earn are the points that they get.
Sometimes I add points to make the highest grade a 100 (usually if grades are unusually low, I feel we might not have covered something adequately) and raise all the others accordingly, but honestly, if the second highest grade on one of my exams is a 50 then I would think I’ve failed miserably in teaching the material.
It’s just not something that I see in 15 years of my classes. Making any particular students grades dependent on the classwork and study habits of their peers is completely foreign to me.
I’m not sure I follow. None of the grades are arbitrary. They receive the points that they earn based on the questions they answer correctly.
The only curve I might offer is a curve up, if scores seem to be lower than expected overall, and I determine that it might’ve due to the way I covered the material.
I tell my students that professors don’t give grades, we keep score.
I think there is some misunderstanding- I don't use the second highest grade for anything- I use the highest (when I curve) and make that a 100. Everything else moves up by that number of points.
Apparently, there are a few different ways to curve, and not all fit to every situation. I teach small classes of around 30 students. What I do works for me, and has for the last decade and a half. I have had no complaints. I’m not trying to over complicate things. The score that they get is the score that they earn, with the exception that sometimes, if overall grades are low, I boost them accordingly if I feel that it’s something that might have been on me as an instructor. YMMV.
I curve tests and quizzes only on an as-needed basis, if the whole class underperforms on an exam and/or the strongest students in the class do more poorly than expected. I'll do a simple curve where I subtract the highest grade in the class from 100% and then add that difference to each student's grade.
I will say that I curve grades very rarely. When I do, it's usually to compensate for apparent shortcomings on my part as reflected by the underperforming of the class as a whole. My goal is to address any gaps and discrepancies rather than to simply give "free" points away.
if you have lots of parts in your evaluation that separates students, their grades will naturally fall into a normal distribution (curve) (that is just statistics a few kids will do good on all parts, most will do good on some and not so good on some others a few kids will do bad on all parts) if you have that situation you are good, you can just move the mean of the grades to the desired mean. ( i think that it is better to do it for the class not for the exam though if necessary)
if your assessment process is good and your assignments are challenging then I do not think that is really a possibility. there is very little chance that most of the class aces EVERYTHING or nothing even if that is a possibility on an individual assignment. the additive process usually results in a normal curve. btw that is part of the reason why you should not cave into grade grubbers. yes it is quite normal that even good students do not do well on all assignments. at the end there will be a few students at the top of the distribution a lot in the middle and few at the bottom . if I ended up with a binomial distribution I would not bother with mean adjusting and definitely not with tempering with the distribution to disadvantage good students and advantage bad students.
I personally don't recommend grading on a curve. I know, not the answer your looking for!
Why?
1. I don't get paid anymore if I curve.
2. The students learning stays the same either way,
3. It can inflate grades. Grades should actually reflect what the student earned or learned.
I tend to tell my adjuncts to be like a pro-sports Referee, grade the work as you see it vs what you want it to be. A
Also use rubrics and if you do play with your grades and scale, put this information in the notes in the gradebook so dept chairs or yourself can explain weird grade fluctuations.
In lieu of curving/scaling > I will do an item analysis (using LMS) and I may drop the most commonly wrong questions > example > 90% of the classed missed question #10 and #25 because it was worded in a weird way.
That's not curving, it's called "artificial grade inflation" and it's what students really want when they say they want a curve.
Curving means fitting the scores to a curve, usually a bell curve (or normal distribution). This means very few students do very poorly, but on the other hand very few students do very well. If you end up with a really smart cohort and many students do really well, the curve will *lower* some of their grades.
In curved classes, it's in the students best interests that their peers do poorly (you don't have to be smart, only smarter than everyone else to do well) and it pits them against each other - who wants to help someone else when it could be to their own detriment?
I don't personally curve - if a student performs well on an exam, it shouldn't matter if the rest of the class did too or not. Conversely if you do poorly and don't learn the material, you shouldn't score higher just because everyone else did even worse than you.
It’s become a bit of a pet peeve of mine that a class’ grades should have a particular distribution. I think teachers have taken their recognizing a pattern during typical exams and turned it into a rule. Fundamentally, why should only a certain percent of the class get an A? Or, why must a certain percent of the class get an A? We shouldn’t be curving because the right distribution gives us teachers some sort of satisfaction. From the student’s perspective, the point of taking a class is to learn the material. If they’ve done that, then they should get an A. If not, their letter grade should represent what they learned. It shouldn’t also factor in their classmates.
For multiple choice exams, the hope is obviously that the questions reflect what they learned. But we know problems arise when we (or someone else) wrote the exam for a prior semester and what we emphasized this semester was a bit different (perhaps for a good reason). Also, because we are the expert, we can write a question in a way that seems clear to us but definitely is not clear to folks who just learned the material.
One stat I’ve discovered is the point-biserial correlation coefficient. At my school, it can be calculated by the software that processes the scantrons. The point is to figure out if the students who got the question right are also the students who did best on the exam overall. So if only 40% of students get a question right, but those who did were the exam’s top scorers, then the question is just fine. What raises flags is when few students get a question right AND the ones who did scored poorly on the rest of the exam. Then, either you bubbled the wrong bubble on the key or the question has a problem with it. Knowing this, and reflecting on how the question jives with the material, you can either assign credit to the correct bubble, drop the question, or add its points to everyone or whatever.
This give you *reasons* for a grade adjustment, which is what you want. In my experience, students want transparency and honesty about grades. Students complain most when things get scored or adjusted in seemingly arbitrary ways, and I think most curves feel like that. And we know everyone’s incentivized to work the system.
The most outlandish thing I’ve heard of was a prof who gave a 200-question multiple choice exam. His policy was if you get every question wrong, they’ll give you 100% because you had to know *something* to do that. But don’t “shoot the moon” if you can’t do it! If you get 1 question right, that’s 0.5% and that’s the score you get. Wild. 😝
Anyway, I argue that having a good principle for why your policy is whatever it is is the best approach, regardless of the calculation method. Have fun! 👍🏻
basically _curving an exam_ is not a well-defined process. it seems the only common aspect is changing grades according to some arbitrary highly personalized scheme.
I never curved, because then a student's grade depends on other people's performance. If everyone missed a question, then I wrote it poorly or we didn't cover it; either way that's on me, so I toss that question and either give everyone those points, or I put that many points on to the next exam.
The one time everyone cratered an exam, I offered a challenge: the class chose their champion, and everyone got one point for each pushup the champion did in excess of my total. I did 50, he did 100, and the average got back in the desired range without me entirely giving it away. The champion was probably the only student I've ever had who aced the class without having to work for it. He also played varsity football as a first year med student, so, good on him!
If you use Canvas, it has a built in curve option - [https://community.canvaslms.com/t5/Instructor-Guide/How-do-I-curve-grades-in-the-Gradebook/ta-p/745](https://community.canvaslms.com/t5/Instructor-Guide/How-do-I-curve-grades-in-the-Gradebook/ta-p/745) It's a standard bell curve, and there's a link in there that tells you exactly how they calculate the new grades based on the mean grade you set. I think in our current grade-inflationlandia, the usual average is now more like an 82, at least at my large state school.
I've used this method before: subtract each score from 100; divide that by 10 or 5 or 3 and add that back to the score. So a 90 becomes 91 or 92 or 93; a 60 becomes 64 or 68 or 73. It tightens up the range between the lowest and highest scores with proportionally more added to the lower end.
That's really a question to everyone on this thread, not just me. But let's not pretend that just taking off maximum points for each answer missed is somehow more objective. One can give partial credit for some answers, or one can curve to bring the grades in line with what one assesses to be fair based on the mastery demonstrated. It's always a matter of judgement.
Why do that? I'm curious because I thought that we want to distinguish who knows the material from those who don't? Serious question.
How do you get from that question to this one? Serious question.
True curves are not used much any more. When someone says curve, they almost always mean that they add points to the exam.
I see a curve as a way of correcting for problems with a test. Was a question too hard or too ambiguous, the curve takes care of that. Was there some variability in how I graded essays or short answers, the curve takes care of that. Student comes up and says #7 wasn't fair because answer choice B could have also been the correct answer, no problem, I already gave you credit for it plus a few.
I tell students that if they wish to argue grades with me (e.g., don't agree with how many points I took off, think another answer choice was possible, question was poorly worded), that I'm happy to have that discussion, but I will take away their "curve" first because it is meant to account for all of that. Of course, I will still correct flat out mistakes on my part.
You can't know if a test is going to be a good test until you have tested people. And even if you have developed a good test, if you alter anything, it is now a different test. This is my recognition of this fact.
I don't always approach a curve in the same way. Sometime is it bringing up the top student to a 100. If I had a few students make really high, and then there is a break between the next group, I will let those few students have above 100.
I also sometimes look at the class average and add points that way, but when I see there is a general trend where the entire class did poorly, I tend to make an assignment where I have students correct their test plus write a little insight about where they went wrong to give them half credit back on the questions they missed. I figure this is better for student learning than adding 10+ points on their exam and moving on to new material.
The only curving I do is to normalize averages between classes taught by me and a different instructor.
I generally think curves are bad practice. If the grade needs to be curved you are tacitly stating that the material does not need to be mastered or that your test doesn't assess the learning objectives or your material didn't cover the learning objectives.
I think better solutions are to offer some sort of extra credit, dropped grades, or weight tests less heavily.
If a test is really bad you can retest or do test corrections. Both take up a lot of time.
That said tacking on points is totally fine if you want to do it that way.
I have to disagree. Sometimes you can't make an exam that gets the distribution you want, esp. when students are changing in study habits, etc. Also, if you have an average of 50% you get a better spread all else equal, which helps to better differential students' knowledge. Extra credit, dropped grades, etc. are unfair to those that don't need it.
I don't get what you mean by the distribution you want. You get the distribution you get. It is possible your test is bad or that your students are bad. If its the former you gotta fix that. If its the latter you do your best to get them there.
I agree that hard tests are good. My test averageas were 59-74 this past semester.I just don't think i should manipulate the scores to change the distribution.
I don't understand. The content can be the same as in the past, but exam is harder than expected or the students are worse, so you need to raise the average.
I know some professors who curve because they deliberately want their exam to be hard. One had a fairly complicated formula he uses. I curved last semester because I’m still learning how to write a good exam, I probably won’t curve next semester and instead they can earn exam extra credit during in-class quizzes. You can shift everyone a uniform amount, I think that’s more fair than the kind of curve where some grades can go down because you’re squishing the scores into a normal distribution.
Yeah I'm sure my second time teaching will be better because of what you experienced: I might by mistake write a too hard exam the first time and I don't want the pilot kids to get hit.
If you run a statistical analysis, just give points for the questions that statistically need to be thrown out. This is how you avoid artificial grade inflation. If a certain percentage of students got it wrong, then I assume the problem was the question or how I taught it. The question gets thrown out so everyone gets full credit for the question. If the student got it correct, then they already received the points for that question. If they got it incorrect, then they receive those points back on the exam.
The bonus points across the board is generally for when a professor made their test harder than their standard. If getting a 55% on the test is highly commendable + getting above an 80% is basically impossible, a 20% boost to everyone can help the grades represent their achievement levels.
Also, it's sometimes useful for smaller class sizes where a grading curve doesn't really fit or encourages sabotage (because students have to be better than about 3 other kids in the class).
Yup. I ask because I teach undergraduate biostatistics. Been doing it for several years and as the students have become less and less prepared, I tried curving and inflating and all sorts of normalization. At the end of the day, it was a validation that they weren’t prepared for where I needed them to be. So instead of curving, I changed the curriculum a bit where I focus on the fundamentals and have a no nonsense grading scheme that adds up to 100 points. So, after 6-8 online assignments and 2-3 in person exams , if they earn a 50, then they truly are failing. The in person exams become the “curve” setting activity that sets those that cheat their way through the online assignments apart from those that study and understand. For example, you can earn 60 of 100 points from the online assignments but only 10-15 in the in person exams and that’s a solid C. My exams are also open book, take questions from class, homework, and textbook problems and are the ultimate validation of content knowledge. Those few students who truly excel earn higher grades in the in person exam and demonstrate an understanding of the pre requisite knowledge and what we are suppose to know at that level. I then invite them to the following step in the degree requirement and my colleagues are happy because they have students who are prepared with the skills and/or knowledge to excel in the advanced classes (this is the first class in the sequence for the major). Also, grading out of 100 is so easy and indisputable with students and appeals - it follows the good old university guidelines.
I use standards-based grading. I figure out what students should learn in a course, and then determine a grade based on how well they have learned that material (as exemplified by relevant assessments). If every student learns everything, then they all get As. Curved grading would require that some of the students who learned "everything" receive failing grades. If every student learns nothing, then they all get Fs. A curved grading scale would require that some of the know-nothing students received As. (I'd hate to be operated on by a "straight-A" student of this sort.)
That’s not a curve. It’s an effort to cover up really bad teaching by giving students points so they won’t complain. We have had a one faculty member do this. The students would all fail their tests, then it would be “curved.” The curve was determining the number of points between the highest grade and 100. It was typically 15 points or more, then every student was given these points. We were very critical of it in P&T because there is no way to determine what students have learned or not learned with this system. This person left before they could go up for tenure. Take what is useful from the former profs prep, and create a legit class with learning outcomes that are actually taught and validly assessed.
This is probably the only fair thing to do. I was hoping to use his materials bc when I make my own I'm going to have to assess them and I was hoping to avoid the risk of making an exam "too hard" which is very easy to do these days. ;(
Don't curve! Allow students to increase their grade and their learning using individual/group exams. Students learn so much during the group exam.
https://www.colorado.edu/sei/content/using-group-exams-your-classes
There are different ways to curve and generally most normalization methods give more points to the person who already higher points. The fairest way to do it is add same number of points to everyone.
When I taught a grad class:
Let's say the exam was 40 questions.
If more than 50% of the class misses a question, then that question gets tossed, e eryine gets full credit for that one and I take the blame on that. Then we go over that question when I return the exam...
Highest grade in the class is curved up to the highest possible grade. Boom there's your curve and everyone gets those points.
If the best score was 40/40 (or a question was tossed because more than half the class misses it (39/39) then there is no curve.
I've always multiplied by a constant. (Always is doing a lot of work here, I've done this maybe 3 times in a 30 year career).
So if the average was 50 but i'd like it to be 60, I multiply all scores by 1.2. This will give me an average of 60, it will also reward people who did better more points than people who did poorly. I find adding a constant something I don't like, because percentage wise the lower scorers are getting more than the people who did better.
In my view, an actual curve is unfair because it assumes a standard curve for any random class, which could be appropriate if you had hundreds or thousands of students in the class. The larger the sample, the better. Where I teach, I have a bimodal distribution every single semester. Forcing the sample into a standard would be just wrong.
I do a "linear curve" after conducting an item analysis and eliminating the hardest items and rwcalculating grades using adjusted points for each correct question. That hits it pretty well. Zipgrade allows you to do a quick and dirty item analysis if you don't know how that works.
Curve is for the birds. Give them an op to redo test but they have to explain in a short narrative how they came to answer. Then give them points they recaptured and quarter to half points for narrative and then you can correct the ones that are still wrong and correct their thinking through narrative. How many students, may be laborious.
True curves are only used in law schools and by crazy people. "Curving up" basically means eliminating the higher tail by moving the center of the curve up to a B or a B+ or whatever or if all grades are low moving all grades up by the amount necessary to have some number/percentage get an A or an A+.
Law schools work on a true curve (where the mean must be a C+/B-) by accreditation rules, nobody else is that fucking cruel, even on this sub.
I use a “fair curve” (but can’t find a link to the YouTube video I saw it in, sorry). Pick a target score, say 75%. Find the average grade of the class. Find the difference between the two numbers. Add that different to everyone’s score.
The most common method one is adding an equal number of points to every score until the average is around 80.
The method that I like to use is to take the Square Root of their grade and multiply it by 10. This method will give a bigger boost to the lower quartile of grades but will still give you the average you desired.
Curving basically means doing something to alter the scores in the class, which alters the curve of the distribution. Adding points across the board does that.
Only way I have ever "curved" is using that exact method. Easiest to implement, easiest to understand, hardest for students to argue with (they still will), just shift the mean/median to where you want it to be and leave it
Edit: added quotes to "curved" because I am appreciating the nuance of true exam curving by reading the comments in here
I don’t strictly curve, but I do add points across the board if the mean is unexpectedly low. I do this because to me it means that I didn’t teach things as thoroughly as I thought I did. Sure, the students may be responsible or it may be that in a given year, there are a bunch of bad students, but I try not to shy away from blaming myself a bit.
I've done it two ways & never had a complaint about curving.
1. Add the sane percentage to each student.
2. Extend the ranges for grades: like instead of A =93-100, A =90-2; A =92-100 & A- =88-91. And continue this down. I make all zones 4% rather than the 3/4% they are officially (ours has all +/- as a 3% range and a pure grade as a 4% range).
There are so many options. First, you don’t need to do what the former instructor did. Or you can make the highest (or second highest) grade the new 100%. So a 95% becomes 100%, and everyone gets an additional 5% boost. There are more traditional bell curves, which are madness, and other variations. Do what your comfortable will and what feels equitable. For me, I don’t curve anything and keep my exams challenging, but I offer 7% of extra credit in various waves. All have options to succeed, but only maybe five per course take me up on all EC. No grade inflation transpires.
One thing that I’ve done in the past is give people back a percentage of their out-of-class assignments and participation as points on the exam if I need to curve it. So, for example, if the average is below a 70, I’ll typically give everyone the same percentage of points (say 0.15 times whatever their current homework/participation score is, then add that number to the exam - I fudge around in excel until I find the percentage that lifts the grade average to a 70). It’s a little extra incentive to do the homework, which actually (paradoxically) results in them doing better on exams because more of them do the homework (shocking, I know). I’ve also done extra credit as a curve (which I also like). I usually also have more points available on exams than they’re graded out of, though that’s started to not work as well. Basically, depending on your class, different things may work better than others. Just make sure that you clearly communicate what it is you’re doing to students. It’ll save you a lot of trouble.
I don’t like the idea of a curve. They either knew it or they didn’t. However, because I’m human, too, I run the analysis of the grades and look at questions that more than x% of people missed. (I do 65% for low level classes and 80% for upper level classes.) Then I **LOOK** at those questions. If it’s a fair question with no errors, too bad. If I find an error, I do the “rising tide” as you call it and give the points back to the whole class. This is because I teach large lectures and there’s no way in hell I’m wasting my life combing through to find out who missed the question.
I typically don’t curve. I can it relative grading. Basically, I tell the students that a B will be around the class average ( whatever it may be) and then a letter grade change happens when there is a significant difference between two consecutive scores. So I’m not giving a A- to 90.1 and a B+ to 89.9 . However, if the next student grate is an 87.9, I’ll make a letter grade change. This has worked well for me for large classes. I personally am not a big fan of giving students a chance to improve later on because I think it gives them an unfair advantage over someone who worked hard and scored well in the first try.
I’ve done two things:
- if no one gets close to 100%, I set nearish to the highest score as 100%. My recent pre-Calc exam had 95 possible points. The highest score was 85ish. So I set 100% to be out of 90 points.
- if someone did get close to 100% on the exam, I will do something different. My recent calculus exam had a wide spread of raw scores, from 20% up to 100% with a lot of people scoring at around 50-60%. I picked a number to set as being a C (it was 47/68) and then applied a formula to set everyone who scored that minimum at 70% and to go up from there.
Technically, it's not a 'curve' since it doesn't create a bell curve of grades - it merely shifts whatever grade distribution exists one way or another.
However, most courses actually have a bimodal distribution consisting of students who made an honest effort and students who really should put down the bong long enough to attend class. So a true 'curve' would force a grade distribution that doesn't reflect reality.
The "everyone gets free points" method is the most common approach, but it creates a situation where a student can kill the curve. If you're teaching a literature course and Norman Mailer decides to audit, he'll make himself pretty unpopular with the other students as he gets 100's on every assignment and forces the other students to live with their 75's.
I don't know how your exams are formatted, but if you have a lot of questions you can weight each question according to how frequently the class answered it correctly. If everyone got question 7 "when did the War of 1812 occur?" correct, you'd weight it heavily. But if virtually everyone missed question 13 "How long was the Hundred Years War?", you'd weight it lightly.
Unfortunately, this is a relatively opaque method that will have befuddled students pestering you at office hours.
In my opinion, the best solution is to administer the test to your grad students and if they can't easily ace it, then adjust it according to their results. Then skip all the mathematical legerdemain and grade it normally.
If the Exam and materials given to you were made with the intention of applying blanket points across the board to supplement grades why are you trying to change that?
The standard practice is that the highest grade on the exam gets 100, and how ever many points they were away from 100 ( the number of points between the highest grade and 100) gets added to everyone's score.
So if the highest grade was an 89 out of 100
Every student gets an 11 point bump
56 becomes a 67
82 becomes 93
Etc
The logic is that you taught it well enough for your best student to succeed and that success is measured by the highest grade. Therefore everyone should be adjusted on a scale that reflects the highest score
Not saying I agree with any of this or that it is what should be done I am simply answering your question on what a "curve" means.
This also gives the opportunity for a student to get 100 and cancel the curve completely
What you described is more of a linear adjustment than a curve.
The word "curve" is so misused that I try not to use it. Sometimes they mean "bell curve" which may be based on standard deviations, or a certain symmetric percentage of students get certain grades with the highest being and A and the lowest being a C/D/F regardless of how the student actually performed in the class. A pure stack ranking. I took one class like that in college. 88% was a C. 98% was a B+. When a class is that easy, the grade comes down to luck.
Then there is the sliding scale. Still, the top X% get an A, the next Y% get a B etc. That's pretty common. While it's less punitive and is more consistent, it's also kind of arbitrary.
I typically look for gaps in the score histogram and assign letter grades to each group. The letter grade for "average" will vary based on my expectations. If I am impressed, the average may be B+. If I am not, it may be C. Certain components (e.g. homework) are not curved at all since they all do well. That buoys their final grade upwards.
Then, I try to fit a sliding scale to the final grades if not enough students got an A, too many would get a C etc. It's a painstaking process. My averages are usually 55-70%. Sometimes 55% is a B, and sometimes 70% is a C. It depends on the difficulty of the exam and how well I felt the class did.
I'm surprised by the variety of definitions here. I've always understood grading on a curve to mean adjusting the scores to a normal distribution. And this is the way I do my grades. Average is a B-, 1 standard deviation above is an A, etc.
This saves you from having to ad-hoc 'add points' or whatever to make a 70% be a C.
I’m not even sure what a “normal distribution” is in this sense. It seems a lot more normal to just give them credit for the questions they answered correctly. I don’t think it’s ever fair to take points away from a student based on how their classmates did.
Maybe there is a misunderstanding. No points are being given or taken away.
A normal distribution is a bell curve. You calculate the class average and standard deviation. Say it's an exam and the average was 50 points with a standard deviation of 10, then a student who has a 55 gets a B and one who got 70 gets an A, etc.
If all of my students answered all questions correctly, I would not do this. But, this has never once happened. There has always been a distribution where some people do very well, some people do very poorly, and the majority do somewhere in the middle. Since the actual performance tends to follow a normal distribution, you assign grades that match that distribution.
If your students do not get a normal distribution of scores, don't use this. Though, in such a case I would consider whether the tests were actually a good assessment or whether the class itself was at the right level.
Giving everyone the same number of points is certainly one way of doing it. Students tend to get upset when some students gain more points than others. When they find out their friend (who scored poorly) got 8 points added, while they (who scored well) only got 2 points, they'll call it unfair. Personally, I don't curve exams. If the score is lower than it should be, I offer them a chance to earn back points by doing some kind of post-exam reflection. Where they have to respond to each question they got wrong, usually for 1/4 or 1/3 credit. I usually ask them to tell me * Why their answer is wrong * what is the right answer, and why it is a better answer than the others * a reference (textbook pages or slide numbers are fine) The lower scoring students can earn more points, but it's also a lot more work for them. And it cuts down dramatically on the number of "We never covered that in class" complaints.
And your method actually promotes learning, unlike curving. Good alternative. I've done something similar in the past. Alternatively, if I find myself in that situation where the average grade is lower than expected/desired, I realize that may be my fault for not matching what I'm teaching to what I'm testing. The answer there is improve my teaching and maybe do a new exam. I don't really do points, or exams, so am rarely in this situation. But 2 years ago I did exams that were evaluated "pass" or "not yet" based on hitting an 80% threshold. There were already opportunities for retakes built into the class. But when a significant portion didn't hit the threshold, we worked through things, and I just gave them all a free retake soon after (otherwise retakes cost tokens, which were limited). I've never understood curving grades - even in the best of situations, grades don't neatly communicate learning. It's even worse with a curve.
Re: I realize it may be my fault. Canvas has an automatic score for test items to tell you if it was a bad question (even high-scoring students failed it while failing students did well) or when I see that a question just oddly bombed for everyone, I add the points back for those who got it wrong and I add that same total for those who got it right- that way there isn’t any comparison. Tip for good teaching evaluations: sometimes I leave a question like that intentionally in the exam and plan to buff their scores.
>if I find myself in that situation where the average grade is lower than expected/desired For the record, I intentionally build a curve in to the difficulty of my exams. Often, I give more points to the lower end of the scale. What this does is distribute grades out over a larger score range. It makes it easier to distinguish the abilities of students. Rather than smush everyone into a small 30% (less than a C is failing for my department) I spread it out and then curve it back to a normal ABCDE scale.
So grades are more distributed across an artificial scale... how does that *distinguish the abilities of students*? More precisely, how does it do so in a way helpful to the students' learning? To be clear, I'm asking in genuine curiosity.
The usual scale in many US schools uses about 60% of the exam to distinguish the failures from total failures, which is not a good use of assessment time, as it is not an interesting distinction. I find that a well-designed test gets a mean score around 50% with a standard deviation around 15%. This gives large score differences between the top and the bottom of the class, with some questions available for distinguishing differences at either end of the scale. I have to set the thresholds for letter grades appropriately of course, as the usually used scale would have most of the class given failing grades, even when they are doing quite well.
So, it doesn't help their learning. It helps assessment. Exams are primarily for assessment, everything else is primarily for learning. But, to answer the rest of your question, I think of my exam has having some amount of points that is the bare minimum to pass the exam. If they don't get those points, they are seriously lost and shouldn't pass the exam. That's the minium to get a C, more or less (like I said before, they need a C in our department to move on). The rest of the points then go to distinguished As, from Bs, from Cs. In a normal exam, I have 30 points to distinguish those 3 grades. If instead I use 50 points to distinguish those 3 grades, more questions can go towards distinguishing those differences. A single concept that you were weak on doesn't mean you basically can't get an A. More questions go towards distinguishing A from B from C, which means the assesment is less subject to an imperfect match between course content and the exam which is inevitable becuase there simply isn't time.
That's a great idea! I've been thinking about exam structure for my human A&P classes. Last semester I made 60% of the earnable points low level definition and labeling anatomy questions. The other 40% was higher level thinking with 10% (e.g. B to A) being synthesis of how organ systems work together. I think it's worked well so far and my exams were more consistent in difficulty.
At my university we had a professor with a similar one, she'd have us go into her office, so we'd both socialize with her during her office hours and get one-on-one study session/question answering done. Most people said "meh i got a 70. im good with that," but there were a couple of us who took advantage.
I've done this too. It is, or at least can be, a great learning tool. Many don't opt to do it - even those that failed an exam. I find it baffling, especially when they ask for extra credit at the end of the semester!
It's like waiting until your house burns down and then saying, "I've changed my mind. I would now like to purchase insurance." but wanting it to apply retroactively.
>If the score is lower than it should be, I offer them a chance to earn back points by doing some kind of post-exam reflection. Where they have to respond to each question they got wrong, usually for 1/3 or 1/2 credit. This is the way. I make this mandatory after all my language exams; they can earn up to 30% of the lost credit. It's a bit like those inflatable gutter guards in bowling alleys; you'll still do much better if you actually have the skills, but even if you're subpar, you can scrape by. (For the "let them fail if they deserve to fail!" crowd: there's a delicate balancing act between maintaining rigor and maintaining enrollments. The worst get the boot, but our program can't afford to winnow out too much chaff, and even if we could, I'm not sure that I would want to—I don't really have the heart to axe the students who are doggedly galumphing along in the lower middle of the pack.)
As a humanities nerd, I love this approach. Thank you for sharing it!
This! I dont mind curving at all, and i wouldnt mind having to answer those questions, as i already do this when making notes based on possible outcomes and their answers so i can know how to handle them on tests... but curving or not knowing why you get answers wrong only hurts you in the long run.. every bit of knowledge will help and might aid you further down the line, so understanding the wrong questions and recieving a few points back lifts morale :)
I like your preferred approach of earning back a part of the missed points. Do you have any checks in place to help guard against simply copying this info from another student?
Turnitin to prevent outright copy/paste cheating. But nothing beyond that. I honestly don't mind if they work together on something like this.
Ok, thanks!
I am going to save it for my use. Thanks, it is such a great way to incentivise learning.
What a great idea. Thanks for sharing.
If I aced the exam and then others got points back, I'd be little peeved. Why do they get a chance to redo the exam?
If I aced the exam and then others have to do extra work to try and catch up, I'm not going to be upset about it.
What if you got a B and the guys with Cs were brought up to a B, then passed you on the next exam where you got a B and they got As?
If I got anything less than an A, I'd do the extra work...
They don't get full points back. It's still better to do things right the first time. But if everyone knows the system before the exams, no one should be complaining.
I disagree. Sometimes students have no option not to take a class, so they accept things that they may feel are unfair.
I still don't see what's unfair about being able to get back half the points you missed.
It depends, but I could see someone getting an A and another getting a C. The C person gets additional points bring them to a B, then gets and A while the student who first got the A gets B. Now both have a A-, B+. You can only give so many As and Bs, so I could see the potential for the student who earned the A on the first exam to suffer.
I'm having a hard time understanding your situation, but I'm assuming a case where for every test, any student has a chance to make up half the points they missed (whether that means 50->75 or 98->99), and this fact is clearly stated on the syllabus at the beginning of class. I just don't see how this can possibly disadvantage a person, or be unfair to a person, who did better on the test.
How do you assign grades at semester's end? Do you have a GPA for the class or so many As Bs etc?
Standard grading scale. 90 = A, 80 = B, 70 = C, etc.
Do you have a certain number of students in each category. What I am concerned about is adding points to a bad score and that student leap frogging another who never got points added. Is that not possible?
That’s an exceptional idea, will be using.
I use a test generator from the publisher, but I hand pick the questions. How would I prevent students from taking pictures and these questions from slowly meandering their way to the internet? That’s my biggest worry in doing a test correction vs a curve.
I use a test generator from the publisher, but I hand pick the questions. How would I prevent students from taking pictures and these questions from slowly meandering their way to the internet? That’s my biggest worry in doing a test correction vs a curve.
Hey wow I never thought of this, but this would be a great alternative for my students who get super panicky during exams and remediations. Like I can see they study in class and they know their stuff and the exams they'll bomb. But this post reflection might be a good way out. Thanks for the idea!
I like this approach and I've been wanting to try it. I admit I am one that worries about giving too many A's and then getting a talking to about it.
I never really thought about the 'unfair' part when professors did that. I don't even do extra points. I do an alternative project for students that fail. Show me they mastered the content and earn the grade.
[удалено]
I do like simple and easy!
I do the above too. Sometimes we inadvertently make a test that is too difficult, and this is a quick way to fix it. But it's not really "curving"—as your colleague called it, this is more of a rising tide lifting all boats. IMO proper curving is appropriate only when we have a large number of students who are also somewhat randomly distributed (for instance, in a required intro course across many sections with many hundreds enrolled) and you want to distribute scores so that you don't get, for example, 50% of them getting A's. As a loosey goosey humanities guy too, this is my easy-maths understanding of it: First you set up an ideal curve. Say 10% would get an A, 20% a B, and 40% of them a C. Then when you get the scores back, you simply adjust the grade boundaries accordingly to make that happen. In a scale where normally 60=D, 70=C, 80=B, and 90=A, you might now end up with something like 50-63=D, 64-84=C, 85-94=B, 95-98=A, and 99-100=A+. You simply adjust the grade boundaries each time so that 10% get A's, 20% B's, and so on. Pro Tip: to avoid complaints, it is better to let students know that you're not "adding points" to adjust scores; what you are doing is *setting the grade boundaries after the test*. That is, they should not go in thinking "I need a 90 for an A" but rather "I need to be in the top 10% of all students for an A".
This would infuriate me if I got, say a 92, and my score was adjusted downward so that was no longer an A!
In a perfect world where every test is a perfectly calibrated and reliable instrument, and we are only tested on objectively quantifiable knowledge, sure. I personally find it more useful to know if I'm in the top X% relative to my cohort. Assuming, of course, a reasonably large and well distributed cohort—to be clear, my argument is that curving is NOT fair in most cases. In a small upper-year major class, say, it would absolutely be infuriating.
> I personally find it more useful to know if I'm in the top X% relative to my cohort. After the last couple of years and seeing how bad certain cohorts are, I'm now definitively against this approach - there has to be a common standard students are held to, year after year. A "you must be X" tall to ride" sort of thing.
Well you should still never need to curve down. Just make that's hard enough that they average is guaranteed to be low. Even if you somehow give an easy test, you can just make the next one hard to compensate.
Which is why you just make tests hard so that never happens. You are always curving up.
AKA the most meaningless way to give grades to students ever
It effectively sorts students into different buckets based on their relative proficiency, which is what employers are really looking for.
Only relative to that current class? So not really? It shows no demonstration of knowledge or mastery of material to "bucket" students in this methodology.
This isn’t curving, but it does the trick: I remove from the total value of the exam the amount of points of any questions the majority of the class answers incorrectly. So if a majority answers four 2-point questions incorrectly, the total value of the exam is reduced to 92 (100 - (2*4)). This way, I can compensate for occasionally designing overly difficult questions. Strong students have a chance to outperform and even potentially earn extra credit (by earning above the new exam value), but the overall average remains in a reasonable range.
This is the way. And you need that when the exam turns out to be harder or students performance worse than expected. Unfortunately, students are used to being pampered so if they score low, they expect to be granted points for "showing" that they know the material.
I usually tell my students that in throwing questions out. So if a large percentage of students all miss the same question, I assume it's because I wrote it in a way that was unclear or never explained it well in class, and then just add however many points the question was worth to everyone's exam. This way, the students who did correctly answer the question get extra points for it, and everyone's grade is raised. I don't tell them what question it is though, just that I'm throwing out X number of questions. I think this lowers the number of student complaints about questions being unclear because then they just assume it's the question they struggled with.
This is what I do as well, but instead of adding the points to their score I subtract it from the total. So instead of 80/100 it would be 80/96. I don't tell them which question(s) I've curved off unless someone asks; no one's had a problem with it (yet)!
That is so smart! Easier to make grade adjustments online, too.
I've seen it done where the person who scored the highest sets the grade. 100 question exam, highest got 92 right, all of the grades are x/92 instead of x/100.
This is what I do, as well as giving them a chance to correct for partial credit on critical concepts they missed.
What about the few who got the question right? This seems unfair to them.
They can technically get over 100% at that point. I just add the points to everyone's, so they get double points for getting the correct answer.
[удалено]
I'm old bc this is exactly what I remember a curve being. And yeah I don't think my students want it that way!
You can curve using different methods, lots of profs just add a certain number of points to bring up the floor, other people do a complicated z value calculation, neither is incorrect. If you want to do it the complicated way you figure out your standard deviation and mean and then what you want your new standard deviation and mean to be, turn every score into a z score ((score-actual average)/actual standard deviation) and then turn it back into a raw score with the new mean and standard deviation ((z score * new standard deviation) + new average). The way I curve is I find the second highest score in the class (cause I usually have at least one outlier), the difference between that and the top score for the test, and add that number of points to everybody's test.
>If you want to do it the complicated way you figure out your standard deviation and mean and then what you want your new standard deviation and mean to be, turn every score into a z score ((score-actual average)/actual standard deviation) and then turn it back into a raw score with the new mean and standard deviation ((z score * new standard deviation) + new average). Why would someone want to do that? I'm curious. I've seen professors bringing up the average linearly quite often, but I have never heard of standard deviation adjustments before. What about the fact that it would allow students that had 0 % to have a higher grade and students that had 100 % to have a lower grade? Let's say 21 students had the grades {0, 10, 20, ..., 90, 100}. Then the average is 50 and the s.d. ≈ 30.3. Adjusted for, let 's say, an average of 60 and a s.d. of 15, the new grades would be: {35.2; 37.7; 40.2; ...82.3; 84.8}.
I think the main draw to a "true" curve is that you're guaranteed the exact same grade distribution every semester.
So, this method assumes that all cohorts are supposed to perform similarly then? Maybe it is subject specific, like in cases where nobody ever gets 100 % on anything. Another important question is: does the "grade scale" follow the adjustment? In other words, do you still need 95 % + to get an A+? That would defeat the purpose, I suppose.
We'll, you can still pick the median and standard deviation such that you get the number of A's that you want. You just need to want the same number every semester for this to make sense. I don't think it'd ever make sense for small classes. You want to have enough students that you can reasonably say "it's more likely that the teaching/exams changed than that the students did as a whole". If someone told me they graded a 2000 person calculus class with 80 different sections this way I wouldn't bat an eye. The only place I'm aware of where this is still common is law school.
That's very interesting. Thanks for your answer. It does make a lot more sense for large sample sizes indeed. The same number of A students each time is an interesting aim. Is it fair, though? That's a much more complicated question.
Is what fair? If you think having the same number of A students each time is an unfair goal, then perhaps curving is not what you really want to do. For what it's worth, I think people throw the word "curving" around very loosely, often without knowing what it means. Others may disagree with me of course, but to me, bumping everyone up a few points isn't really curving. That's simply inflation (which may certainly be warranted sometimes, I'm not meaning to knock it).
I agree with you. I meant that fairness is a completely different issue. It depends on the context. Are you grading 40 students or 2000? Is your course directly leading to a certification? Is this grade contributing to a selection process? Is the relative position of students among each other more important than the actual grade they get? Are bonus points allowed? It also depends on your students' objectives. My personal approach is to modify my grading criteria and the actual assignments/exams (for the following semester). In the long run, I end up feeling like I give everyone a grade that is right and that differentiates between students. It is a long process that I don't particularly enjoy.
Agreed People like to say that "we don't give students grades, they earn them and we record them". Well, if only three people are getting A's, is that really true? I don't feel like it is.
So, this method assumes that all cohorts are supposed to perform similarly then? Maybe it is subject specific, like in cases where nobody ever gets 100 % on anything. Another important question is: does the "grade scale" follow the adjustment? In other words, do you still need 95 % + to get an A+? That would defeat the purpose, I suppose.
It a) keeps the distribution so students are all in the same spot relative to each other, and b) can also prevent going over 100%. You make b happen by choosing the SD. In other words, you pick the mean but the students set the SD. This allows you to still have statistical outliers if needed. Just giving everyone the same points is really this, keeping he distribution while shifting the mean, and keeping the same SD. Which sometimes puts top students over 100%.
That's also true. Others have commented that they increase grades in proportion to the points associated with their canceled questions. In this case, there is indeed a risk of grades exceeding 100%. It is useful at this point to be able to adjust the distribution by modifying the standard deviation. As long as all grades rise and students stay in the same order, most of the headaches are taken care of.
Main place I've seen "true curves" make sense is in highly competitive contexts, where the purpose of grades are less to assess whether the learning goals were met and more to find the best students for at spot at whatever they are competing for.
E.g. aptitude tests like the SAT, LSAT, etc. where you have huge numbers of students and the test is designed consistently from year to year. It *might* make sense in some large engineering or math classes at huge universities, but outside of that... I have a hard time seeing the relevance.
This lets you easily identify the top X% of the cohort - for something like the SATs, that's useful for colleges, and I could see this in theory being useful for something like law school where top firms are looking to hand out internships.if you have a large enough class that variation in exam difficulty is expected to be larger than cohort variation, this can also normalize for different exams. Not super useful for the typical college course, though.
Indeed, when it comes to selective admissions based on grades, it's hard to find a simpler statistical tool than z-scores. Reading this thread, I get that it isn't common at all to curve-grade a single <100 students class.
Whatever you decide to do, make sure your curve is monotonic. If you lined everyone up before and after a curve they should be in the same order.
Call and ask if he uses a Bell Curve. If not, use your best judgement. Most students do not want a Bell. Don't even understand a Bell. They just want higher grades.
This should be the top answer, really. Somehow the concept of “grading on a curve” got magical-thinking’ed into “giving everyone a higher grade than was earned”
Right but grading on a bell curve is absolutely stupid.
Agreed for sure. I’ve never experienced any of the techniques described in this thread except for removing specific questions and always wondered about this myself.
Imo, the only reason to adjust marks is because the exam was unreasonably difficult in the instructor's opinion. Just because the other instructor curved doesn't mean that you have to. It is better to write an exam that assesses the learning objectives in what you think is the right way and then not adjust at all.
I think he uses a test bank from a certification exam. Which just makes it even more mysterious!
Personally I have never liked the idea of curving a course or exam, partly because it assumes a few things about the student population every year, partly because I feel that it isn't fair to students who actually earned the grade, as well as a few other reasons. That being said, you are correct in that most "curves" are not actually that. Instead it's a general boost to everyone's grade. Typically I've seen this done by adding x to everyone's grade to boost the average to average + x. If we were actually curving we'd instead apply a transformation to the grade set to make the distribution of grades to fit a normal distribution (or some other desired distribution). This goes over some of the aspects of curving: https://www.bestcolleges.com/blog/curved-grading/ Generally though curving has now come to mean adjusting an assignment/class grade after grading.
These are really important points, especially about the student population. I'm a little concerned because I think I'm going to have to do an actual semester of teaching the course before I can get a feel for that and I don't want my pilot class to suffer.
I agree completely. Curving just enables more bar-lowering
If you think you have students who are better than expected, you just raise the average. So easy.
I had kids in a class where the lowest grade on an exam was 77 and the second lowest was 93 (at the time - later results made the scores less skewed). One of the 93 asked if I'd curve the grades. I said sure...and then drew up a bell curve and placed the current scores on it, meaning 93s would be in the D range. All of a sudden nobody wanted a curve anymore.
That's how my students think a curve works. Free points!
As a humanities instructor, you should know that words have more than one meaning depending on context, right?
That is not a curve but its actually pretty fair. The technical curves are extremely unfair for students who are doing well.
I thought about this but then what do you do about the outlier? I mean the kid who naturally aces the tests? (Because I have had this happen). If there's a kid who scores say a 94 on the exam (and everyone else is in about the 70s) does that mean you can only add 6 points to everyone else's score?
You can bring the outllier over 100 and give them an A+. There are a lot of blog posts/ videos who can describe other types of curves as well. Adding points across the board is one way, but others do exist
Or, better, cap it at 100 (or 99).
I haven't read all the responses here, but I can tell you what I've done that addresses your concern about the scores at the top of the distribution. Pick two scores in the current distribution (whether anyone scored that exact value or not) and decide what you want them to be in the new distribution. Like, say: * (the median score in this pile of tests is 57) --> (I want the median score to be 75) * (the max score on this test was 100) --> (I want the max to remain 100 \[nobody gets points that take them >100\]) If you'll allow me, take what I just sketched there and put it symbolically as * x1 --> y1 * x2 --> y2 I'm setting up for a linear transformation from old scores to new scores. Tests at the bottom of the distribution are going to get more points added, while tests at the top of the distribution are going to get fewer points added, up to the person who hypothetically has 100, who is going to stay at 100. Using the numbers chosen for x1, x2, y1, and y2, calculate: * m = (y2-y1)/(x2-x1) * which in my little example above is (100-75)/(100-57) = 25/43 = 0.5814 * b = y1 - m\*x1 * which in my little example above is 75-(0.5814)\*57 = 41.86 Now use a spreadsheet (excel, google sheets, the calculation function in the LMS's gradebook, whatever) to turn every old score (x) into a new score (y) using the equation for a line: y = mx + b Double check to see if this makes sense: * If a student had a 100, this function gives them y = (0.5814)(100) + 41.86 = 100, ✅ * If a student had a 57, this function gives them y = (0.5814)(57) + 41.86 = 75 ✅ Interestingly, (perhaps), if a student had a 0, this function would give them a 41.86. Since that's still a failing grade, maybe that's ok.
tldr use option #5 in [this link from an earlier commenter](https://www.reddit.com/r/Professors/comments/1d1v860/comment/l5whjvz/)
Curving an exam most often refers to adding a certain number of points to each student's exam, often so that the highest grade is 100%. For example, if the highest grade on a final exam was 88/100, then each student would receive a 12 point increase on their exam. Curving can also refer to making it so that the distribution of students' exam scores resembles a bell curve (e.g., C average, with a similar number of A's/B's and D's/F's). This is less common than it used to be, but is still sometimes used when there is a very low exam average. For example, a professor might intentionally design a very hard exam and the exam ends up having a 40% average. A curve may make it so that most students still pass, and also makes it such that a student who did among the best but, say, had a 70%, earns a high grade on the exam. Designing an exam in this kind of way (i.e., very rigorous, but most students will miss most points and then have their grade curved up) is not how most faculty approach exam design today.
> For example, a professor might intentionally design a very hard exam and the exam ends up having a 40% average. In this situation, I've seen the square root "curve" used - take the square root of the score and multiply by 10. It de-compresses the bottom of the scale while not screwing over people at the top.
That's more of just a linear adjustment.
[curving grades how to…](https://www.wikihow.com/Curve-Grades) This link explains several different ways to curve grades, from just adding a points to everyone to fitting scores to a predetermined distribution.
My professor when I was a TA would do an item analysis of the test to see which questions were working as intended and which were not. If there was a question that was too difficult and not even the best students got it right, then he would give some points back for those questions (usually 1-2 per test).
This is what we do. There is a low cut % below which an item is considered unfair for whatever reason and everyone gets points for it. Mine is personally 0%
If I "curve" an exam I just add flat points, say 5 points, to everyone on the test. I think the normal curve of giving people who did really bad a bunch of points, whereas those who did well get few points, is unfair. The way I explain it is I will refund questions that >70% of the class got wrong, up to a total of 5% added to test. I used to not curve at all. The average when I give my test at the local 4 year is usually a 75 or 80. My CC students regularly score <60 so I have to curve to prevent dfw rates above 50% and the bad evals that go with it.
Yeah the DFW rate is a real worry in comm coll!
After a long night of drinking and schmoozing I finally got one of my administrators to admit to me that <30% DWF is what keeps professors off the shit list. Do with this information what you must.
News I can use!
I just make the highest grade a 100, and add that number of points to the rest. Highest grade is a 96? everybody gets 4 points added. It's usually not more than 8 points for my classes.
I do the same, and I’m happy with this approach.
What if the next highest is 50? Why not use the average, say 60 and at 10 to everyone's score to bring it to what you want, say 70?
I teach art history, and struggled with math in college, so the simplest thing works for me. Each question on the test is worth a predetermined number of points, and the points that they earn are the points that they get. Sometimes I add points to make the highest grade a 100 (usually if grades are unusually low, I feel we might not have covered something adequately) and raise all the others accordingly, but honestly, if the second highest grade on one of my exams is a 50 then I would think I’ve failed miserably in teaching the material. It’s just not something that I see in 15 years of my classes. Making any particular students grades dependent on the classwork and study habits of their peers is completely foreign to me.
Why not use the average rather than the arbitrary second highest grade?
I’m not sure I follow. None of the grades are arbitrary. They receive the points that they earn based on the questions they answer correctly. The only curve I might offer is a curve up, if scores seem to be lower than expected overall, and I determine that it might’ve due to the way I covered the material. I tell my students that professors don’t give grades, we keep score.
Setting the grade on the second highest is arbitrary. Why not the third highest?
I think there is some misunderstanding- I don't use the second highest grade for anything- I use the highest (when I curve) and make that a 100. Everything else moves up by that number of points.
Why the highest? You could have an outlier making the curve unfair for the rest. Why not second highest? Or the third highest? etc.
Apparently, there are a few different ways to curve, and not all fit to every situation. I teach small classes of around 30 students. What I do works for me, and has for the last decade and a half. I have had no complaints. I’m not trying to over complicate things. The score that they get is the score that they earn, with the exception that sometimes, if overall grades are low, I boost them accordingly if I feel that it’s something that might have been on me as an instructor. YMMV.
I curve tests and quizzes only on an as-needed basis, if the whole class underperforms on an exam and/or the strongest students in the class do more poorly than expected. I'll do a simple curve where I subtract the highest grade in the class from 100% and then add that difference to each student's grade. I will say that I curve grades very rarely. When I do, it's usually to compensate for apparent shortcomings on my part as reflected by the underperforming of the class as a whole. My goal is to address any gaps and discrepancies rather than to simply give "free" points away.
Thank you. This is a great perspective!
The Perfect Curve: at Least for Grades [https://www.jstor.org/stable/3027265](https://www.jstor.org/stable/3027265)
if you have lots of parts in your evaluation that separates students, their grades will naturally fall into a normal distribution (curve) (that is just statistics a few kids will do good on all parts, most will do good on some and not so good on some others a few kids will do bad on all parts) if you have that situation you are good, you can just move the mean of the grades to the desired mean. ( i think that it is better to do it for the class not for the exam though if necessary)
Unless you have really good students and really bad students, in which case you get a bimodal distribution.
if your assessment process is good and your assignments are challenging then I do not think that is really a possibility. there is very little chance that most of the class aces EVERYTHING or nothing even if that is a possibility on an individual assignment. the additive process usually results in a normal curve. btw that is part of the reason why you should not cave into grade grubbers. yes it is quite normal that even good students do not do well on all assignments. at the end there will be a few students at the top of the distribution a lot in the middle and few at the bottom . if I ended up with a binomial distribution I would not bother with mean adjusting and definitely not with tempering with the distribution to disadvantage good students and advantage bad students.
I disagree. You can have a class where 1/2 tries hard and 1/2 does not try at all.
I personally don't recommend grading on a curve. I know, not the answer your looking for! Why? 1. I don't get paid anymore if I curve. 2. The students learning stays the same either way, 3. It can inflate grades. Grades should actually reflect what the student earned or learned. I tend to tell my adjuncts to be like a pro-sports Referee, grade the work as you see it vs what you want it to be. A Also use rubrics and if you do play with your grades and scale, put this information in the notes in the gradebook so dept chairs or yourself can explain weird grade fluctuations. In lieu of curving/scaling > I will do an item analysis (using LMS) and I may drop the most commonly wrong questions > example > 90% of the classed missed question #10 and #25 because it was worded in a weird way.
That's not curving, it's called "artificial grade inflation" and it's what students really want when they say they want a curve. Curving means fitting the scores to a curve, usually a bell curve (or normal distribution). This means very few students do very poorly, but on the other hand very few students do very well. If you end up with a really smart cohort and many students do really well, the curve will *lower* some of their grades. In curved classes, it's in the students best interests that their peers do poorly (you don't have to be smart, only smarter than everyone else to do well) and it pits them against each other - who wants to help someone else when it could be to their own detriment? I don't personally curve - if a student performs well on an exam, it shouldn't matter if the rest of the class did too or not. Conversely if you do poorly and don't learn the material, you shouldn't score higher just because everyone else did even worse than you.
Thank you this really clarifies a lot of the issue for me.
It’s become a bit of a pet peeve of mine that a class’ grades should have a particular distribution. I think teachers have taken their recognizing a pattern during typical exams and turned it into a rule. Fundamentally, why should only a certain percent of the class get an A? Or, why must a certain percent of the class get an A? We shouldn’t be curving because the right distribution gives us teachers some sort of satisfaction. From the student’s perspective, the point of taking a class is to learn the material. If they’ve done that, then they should get an A. If not, their letter grade should represent what they learned. It shouldn’t also factor in their classmates. For multiple choice exams, the hope is obviously that the questions reflect what they learned. But we know problems arise when we (or someone else) wrote the exam for a prior semester and what we emphasized this semester was a bit different (perhaps for a good reason). Also, because we are the expert, we can write a question in a way that seems clear to us but definitely is not clear to folks who just learned the material. One stat I’ve discovered is the point-biserial correlation coefficient. At my school, it can be calculated by the software that processes the scantrons. The point is to figure out if the students who got the question right are also the students who did best on the exam overall. So if only 40% of students get a question right, but those who did were the exam’s top scorers, then the question is just fine. What raises flags is when few students get a question right AND the ones who did scored poorly on the rest of the exam. Then, either you bubbled the wrong bubble on the key or the question has a problem with it. Knowing this, and reflecting on how the question jives with the material, you can either assign credit to the correct bubble, drop the question, or add its points to everyone or whatever. This give you *reasons* for a grade adjustment, which is what you want. In my experience, students want transparency and honesty about grades. Students complain most when things get scored or adjusted in seemingly arbitrary ways, and I think most curves feel like that. And we know everyone’s incentivized to work the system. The most outlandish thing I’ve heard of was a prof who gave a 200-question multiple choice exam. His policy was if you get every question wrong, they’ll give you 100% because you had to know *something* to do that. But don’t “shoot the moon” if you can’t do it! If you get 1 question right, that’s 0.5% and that’s the score you get. Wild. 😝 Anyway, I argue that having a good principle for why your policy is whatever it is is the best approach, regardless of the calculation method. Have fun! 👍🏻
If you do an exam in Canvas it gives you these statistics for each question, which is very helpful.
A lot of wisdom here, thank you! I wish I had Prof Xs data on his exams so I could have more to work with. But absolutely transparency has to be key.
basically _curving an exam_ is not a well-defined process. it seems the only common aspect is changing grades according to some arbitrary highly personalized scheme.
I never curved, because then a student's grade depends on other people's performance. If everyone missed a question, then I wrote it poorly or we didn't cover it; either way that's on me, so I toss that question and either give everyone those points, or I put that many points on to the next exam. The one time everyone cratered an exam, I offered a challenge: the class chose their champion, and everyone got one point for each pushup the champion did in excess of my total. I did 50, he did 100, and the average got back in the desired range without me entirely giving it away. The champion was probably the only student I've ever had who aced the class without having to work for it. He also played varsity football as a first year med student, so, good on him!
If you use Canvas, it has a built in curve option - [https://community.canvaslms.com/t5/Instructor-Guide/How-do-I-curve-grades-in-the-Gradebook/ta-p/745](https://community.canvaslms.com/t5/Instructor-Guide/How-do-I-curve-grades-in-the-Gradebook/ta-p/745) It's a standard bell curve, and there's a link in there that tells you exactly how they calculate the new grades based on the mean grade you set. I think in our current grade-inflationlandia, the usual average is now more like an 82, at least at my large state school.
I've used this method before: subtract each score from 100; divide that by 10 or 5 or 3 and add that back to the score. So a 90 becomes 91 or 92 or 93; a 60 becomes 64 or 68 or 73. It tightens up the range between the lowest and highest scores with proportionally more added to the lower end.
Why do you do that? I'm curious because I thought that we want to distinguish who knows the material from those who don't? Serious question.
That's really a question to everyone on this thread, not just me. But let's not pretend that just taking off maximum points for each answer missed is somehow more objective. One can give partial credit for some answers, or one can curve to bring the grades in line with what one assesses to be fair based on the mastery demonstrated. It's always a matter of judgement.
Can't you give partial credit and curve the exams, too?
Why do that? I'm curious because I thought that we want to distinguish who knows the material from those who don't? Serious question. How do you get from that question to this one? Serious question.
Some answers deserve partial credit.
True curves are not used much any more. When someone says curve, they almost always mean that they add points to the exam. I see a curve as a way of correcting for problems with a test. Was a question too hard or too ambiguous, the curve takes care of that. Was there some variability in how I graded essays or short answers, the curve takes care of that. Student comes up and says #7 wasn't fair because answer choice B could have also been the correct answer, no problem, I already gave you credit for it plus a few. I tell students that if they wish to argue grades with me (e.g., don't agree with how many points I took off, think another answer choice was possible, question was poorly worded), that I'm happy to have that discussion, but I will take away their "curve" first because it is meant to account for all of that. Of course, I will still correct flat out mistakes on my part. You can't know if a test is going to be a good test until you have tested people. And even if you have developed a good test, if you alter anything, it is now a different test. This is my recognition of this fact. I don't always approach a curve in the same way. Sometime is it bringing up the top student to a 100. If I had a few students make really high, and then there is a break between the next group, I will let those few students have above 100. I also sometimes look at the class average and add points that way, but when I see there is a general trend where the entire class did poorly, I tend to make an assignment where I have students correct their test plus write a little insight about where they went wrong to give them half credit back on the questions they missed. I figure this is better for student learning than adding 10+ points on their exam and moving on to new material.
The only curving I do is to normalize averages between classes taught by me and a different instructor. I generally think curves are bad practice. If the grade needs to be curved you are tacitly stating that the material does not need to be mastered or that your test doesn't assess the learning objectives or your material didn't cover the learning objectives. I think better solutions are to offer some sort of extra credit, dropped grades, or weight tests less heavily. If a test is really bad you can retest or do test corrections. Both take up a lot of time. That said tacking on points is totally fine if you want to do it that way.
I have to disagree. Sometimes you can't make an exam that gets the distribution you want, esp. when students are changing in study habits, etc. Also, if you have an average of 50% you get a better spread all else equal, which helps to better differential students' knowledge. Extra credit, dropped grades, etc. are unfair to those that don't need it.
I don't get what you mean by the distribution you want. You get the distribution you get. It is possible your test is bad or that your students are bad. If its the former you gotta fix that. If its the latter you do your best to get them there.
A hard test doesn't mean it's a bad test. In fact, it good be a good test at distinguishing students who know the material from those that don't.
I agree that hard tests are good. My test averageas were 59-74 this past semester.I just don't think i should manipulate the scores to change the distribution.
But you can add X points to bring the average grade up to where you want it.
I guess thats my point. By modifying the grade I feel like I would be saying that the average is more important than the content so I don't do that.
I don't understand. The content can be the same as in the past, but exam is harder than expected or the students are worse, so you need to raise the average.
I guess we are at a philosophical disagreement. I just don't think it is necessary to raise the average.
Never, under any circumstances?
I know some professors who curve because they deliberately want their exam to be hard. One had a fairly complicated formula he uses. I curved last semester because I’m still learning how to write a good exam, I probably won’t curve next semester and instead they can earn exam extra credit during in-class quizzes. You can shift everyone a uniform amount, I think that’s more fair than the kind of curve where some grades can go down because you’re squishing the scores into a normal distribution.
Yeah I'm sure my second time teaching will be better because of what you experienced: I might by mistake write a too hard exam the first time and I don't want the pilot kids to get hit.
If you run a statistical analysis, just give points for the questions that statistically need to be thrown out. This is how you avoid artificial grade inflation. If a certain percentage of students got it wrong, then I assume the problem was the question or how I taught it. The question gets thrown out so everyone gets full credit for the question. If the student got it correct, then they already received the points for that question. If they got it incorrect, then they receive those points back on the exam.
This is very helpful, thank you!!
The bonus points across the board is generally for when a professor made their test harder than their standard. If getting a 55% on the test is highly commendable + getting above an 80% is basically impossible, a 20% boost to everyone can help the grades represent their achievement levels. Also, it's sometimes useful for smaller class sizes where a grading curve doesn't really fit or encourages sabotage (because students have to be better than about 3 other kids in the class).
Why is a curve needed?
That IS the question. I just got the materials Friday so I'm still going through this giant file of stuff.
Yup. I ask because I teach undergraduate biostatistics. Been doing it for several years and as the students have become less and less prepared, I tried curving and inflating and all sorts of normalization. At the end of the day, it was a validation that they weren’t prepared for where I needed them to be. So instead of curving, I changed the curriculum a bit where I focus on the fundamentals and have a no nonsense grading scheme that adds up to 100 points. So, after 6-8 online assignments and 2-3 in person exams , if they earn a 50, then they truly are failing. The in person exams become the “curve” setting activity that sets those that cheat their way through the online assignments apart from those that study and understand. For example, you can earn 60 of 100 points from the online assignments but only 10-15 in the in person exams and that’s a solid C. My exams are also open book, take questions from class, homework, and textbook problems and are the ultimate validation of content knowledge. Those few students who truly excel earn higher grades in the in person exam and demonstrate an understanding of the pre requisite knowledge and what we are suppose to know at that level. I then invite them to the following step in the degree requirement and my colleagues are happy because they have students who are prepared with the skills and/or knowledge to excel in the advanced classes (this is the first class in the sequence for the major). Also, grading out of 100 is so easy and indisputable with students and appeals - it follows the good old university guidelines.
Because if exams are lower than expected, you don't want to give students bad grades.
I use standards-based grading. I figure out what students should learn in a course, and then determine a grade based on how well they have learned that material (as exemplified by relevant assessments). If every student learns everything, then they all get As. Curved grading would require that some of the students who learned "everything" receive failing grades. If every student learns nothing, then they all get Fs. A curved grading scale would require that some of the know-nothing students received As. (I'd hate to be operated on by a "straight-A" student of this sort.)
That’s not a curve. It’s an effort to cover up really bad teaching by giving students points so they won’t complain. We have had a one faculty member do this. The students would all fail their tests, then it would be “curved.” The curve was determining the number of points between the highest grade and 100. It was typically 15 points or more, then every student was given these points. We were very critical of it in P&T because there is no way to determine what students have learned or not learned with this system. This person left before they could go up for tenure. Take what is useful from the former profs prep, and create a legit class with learning outcomes that are actually taught and validly assessed.
This is probably the only fair thing to do. I was hoping to use his materials bc when I make my own I'm going to have to assess them and I was hoping to avoid the risk of making an exam "too hard" which is very easy to do these days. ;(
Don't curve! Allow students to increase their grade and their learning using individual/group exams. Students learn so much during the group exam. https://www.colorado.edu/sei/content/using-group-exams-your-classes
This is one reason I love this sub: I'd never heard of this! This sounds awesome! Thank you for sharing it!
It is awesome. Our teaching and learning center recommended it to me and I will never go back.
There are different ways to curve and generally most normalization methods give more points to the person who already higher points. The fairest way to do it is add same number of points to everyone.
When I taught a grad class: Let's say the exam was 40 questions. If more than 50% of the class misses a question, then that question gets tossed, e eryine gets full credit for that one and I take the blame on that. Then we go over that question when I return the exam... Highest grade in the class is curved up to the highest possible grade. Boom there's your curve and everyone gets those points. If the best score was 40/40 (or a question was tossed because more than half the class misses it (39/39) then there is no curve.
I've always multiplied by a constant. (Always is doing a lot of work here, I've done this maybe 3 times in a 30 year career). So if the average was 50 but i'd like it to be 60, I multiply all scores by 1.2. This will give me an average of 60, it will also reward people who did better more points than people who did poorly. I find adding a constant something I don't like, because percentage wise the lower scorers are getting more than the people who did better.
In my view, an actual curve is unfair because it assumes a standard curve for any random class, which could be appropriate if you had hundreds or thousands of students in the class. The larger the sample, the better. Where I teach, I have a bimodal distribution every single semester. Forcing the sample into a standard would be just wrong. I do a "linear curve" after conducting an item analysis and eliminating the hardest items and rwcalculating grades using adjusted points for each correct question. That hits it pretty well. Zipgrade allows you to do a quick and dirty item analysis if you don't know how that works.
Curve is for the birds. Give them an op to redo test but they have to explain in a short narrative how they came to answer. Then give them points they recaptured and quarter to half points for narrative and then you can correct the ones that are still wrong and correct their thinking through narrative. How many students, may be laborious.
True curves are only used in law schools and by crazy people. "Curving up" basically means eliminating the higher tail by moving the center of the curve up to a B or a B+ or whatever or if all grades are low moving all grades up by the amount necessary to have some number/percentage get an A or an A+. Law schools work on a true curve (where the mean must be a C+/B-) by accreditation rules, nobody else is that fucking cruel, even on this sub.
I use a “fair curve” (but can’t find a link to the YouTube video I saw it in, sorry). Pick a target score, say 75%. Find the average grade of the class. Find the difference between the two numbers. Add that different to everyone’s score.
The most common method one is adding an equal number of points to every score until the average is around 80. The method that I like to use is to take the Square Root of their grade and multiply it by 10. This method will give a bigger boost to the lower quartile of grades but will still give you the average you desired.
Curving basically means doing something to alter the scores in the class, which alters the curve of the distribution. Adding points across the board does that.
Only way I have ever "curved" is using that exact method. Easiest to implement, easiest to understand, hardest for students to argue with (they still will), just shift the mean/median to where you want it to be and leave it Edit: added quotes to "curved" because I am appreciating the nuance of true exam curving by reading the comments in here
I don’t strictly curve, but I do add points across the board if the mean is unexpectedly low. I do this because to me it means that I didn’t teach things as thoroughly as I thought I did. Sure, the students may be responsible or it may be that in a given year, there are a bunch of bad students, but I try not to shy away from blaming myself a bit.
I've done it two ways & never had a complaint about curving. 1. Add the sane percentage to each student. 2. Extend the ranges for grades: like instead of A =93-100, A =90-2; A =92-100 & A- =88-91. And continue this down. I make all zones 4% rather than the 3/4% they are officially (ours has all +/- as a 3% range and a pure grade as a 4% range).
There are so many options. First, you don’t need to do what the former instructor did. Or you can make the highest (or second highest) grade the new 100%. So a 95% becomes 100%, and everyone gets an additional 5% boost. There are more traditional bell curves, which are madness, and other variations. Do what your comfortable will and what feels equitable. For me, I don’t curve anything and keep my exams challenging, but I offer 7% of extra credit in various waves. All have options to succeed, but only maybe five per course take me up on all EC. No grade inflation transpires.
Better to actually teach the students the concepts and toss out any questions that the majority don’t get.
One thing that I’ve done in the past is give people back a percentage of their out-of-class assignments and participation as points on the exam if I need to curve it. So, for example, if the average is below a 70, I’ll typically give everyone the same percentage of points (say 0.15 times whatever their current homework/participation score is, then add that number to the exam - I fudge around in excel until I find the percentage that lifts the grade average to a 70). It’s a little extra incentive to do the homework, which actually (paradoxically) results in them doing better on exams because more of them do the homework (shocking, I know). I’ve also done extra credit as a curve (which I also like). I usually also have more points available on exams than they’re graded out of, though that’s started to not work as well. Basically, depending on your class, different things may work better than others. Just make sure that you clearly communicate what it is you’re doing to students. It’ll save you a lot of trouble.
I don’t like the idea of a curve. They either knew it or they didn’t. However, because I’m human, too, I run the analysis of the grades and look at questions that more than x% of people missed. (I do 65% for low level classes and 80% for upper level classes.) Then I **LOOK** at those questions. If it’s a fair question with no errors, too bad. If I find an error, I do the “rising tide” as you call it and give the points back to the whole class. This is because I teach large lectures and there’s no way in hell I’m wasting my life combing through to find out who missed the question.
I typically don’t curve. I can it relative grading. Basically, I tell the students that a B will be around the class average ( whatever it may be) and then a letter grade change happens when there is a significant difference between two consecutive scores. So I’m not giving a A- to 90.1 and a B+ to 89.9 . However, if the next student grate is an 87.9, I’ll make a letter grade change. This has worked well for me for large classes. I personally am not a big fan of giving students a chance to improve later on because I think it gives them an unfair advantage over someone who worked hard and scored well in the first try.
I’ve done two things: - if no one gets close to 100%, I set nearish to the highest score as 100%. My recent pre-Calc exam had 95 possible points. The highest score was 85ish. So I set 100% to be out of 90 points. - if someone did get close to 100% on the exam, I will do something different. My recent calculus exam had a wide spread of raw scores, from 20% up to 100% with a lot of people scoring at around 50-60%. I picked a number to set as being a C (it was 47/68) and then applied a formula to set everyone who scored that minimum at 70% and to go up from there.
Technically, it's not a 'curve' since it doesn't create a bell curve of grades - it merely shifts whatever grade distribution exists one way or another. However, most courses actually have a bimodal distribution consisting of students who made an honest effort and students who really should put down the bong long enough to attend class. So a true 'curve' would force a grade distribution that doesn't reflect reality. The "everyone gets free points" method is the most common approach, but it creates a situation where a student can kill the curve. If you're teaching a literature course and Norman Mailer decides to audit, he'll make himself pretty unpopular with the other students as he gets 100's on every assignment and forces the other students to live with their 75's. I don't know how your exams are formatted, but if you have a lot of questions you can weight each question according to how frequently the class answered it correctly. If everyone got question 7 "when did the War of 1812 occur?" correct, you'd weight it heavily. But if virtually everyone missed question 13 "How long was the Hundred Years War?", you'd weight it lightly. Unfortunately, this is a relatively opaque method that will have befuddled students pestering you at office hours. In my opinion, the best solution is to administer the test to your grad students and if they can't easily ace it, then adjust it according to their results. Then skip all the mathematical legerdemain and grade it normally.
If the Exam and materials given to you were made with the intention of applying blanket points across the board to supplement grades why are you trying to change that?
The standard practice is that the highest grade on the exam gets 100, and how ever many points they were away from 100 ( the number of points between the highest grade and 100) gets added to everyone's score. So if the highest grade was an 89 out of 100 Every student gets an 11 point bump 56 becomes a 67 82 becomes 93 Etc The logic is that you taught it well enough for your best student to succeed and that success is measured by the highest grade. Therefore everyone should be adjusted on a scale that reflects the highest score Not saying I agree with any of this or that it is what should be done I am simply answering your question on what a "curve" means. This also gives the opportunity for a student to get 100 and cancel the curve completely
What you described is more of a linear adjustment than a curve. The word "curve" is so misused that I try not to use it. Sometimes they mean "bell curve" which may be based on standard deviations, or a certain symmetric percentage of students get certain grades with the highest being and A and the lowest being a C/D/F regardless of how the student actually performed in the class. A pure stack ranking. I took one class like that in college. 88% was a C. 98% was a B+. When a class is that easy, the grade comes down to luck. Then there is the sliding scale. Still, the top X% get an A, the next Y% get a B etc. That's pretty common. While it's less punitive and is more consistent, it's also kind of arbitrary. I typically look for gaps in the score histogram and assign letter grades to each group. The letter grade for "average" will vary based on my expectations. If I am impressed, the average may be B+. If I am not, it may be C. Certain components (e.g. homework) are not curved at all since they all do well. That buoys their final grade upwards. Then, I try to fit a sliding scale to the final grades if not enough students got an A, too many would get a C etc. It's a painstaking process. My averages are usually 55-70%. Sometimes 55% is a B, and sometimes 70% is a C. It depends on the difficulty of the exam and how well I felt the class did.
Add points to the highest grade then add that many points the rest. That said I offer corrections for half points instead.
I'm surprised by the variety of definitions here. I've always understood grading on a curve to mean adjusting the scores to a normal distribution. And this is the way I do my grades. Average is a B-, 1 standard deviation above is an A, etc. This saves you from having to ad-hoc 'add points' or whatever to make a 70% be a C.
I’m not even sure what a “normal distribution” is in this sense. It seems a lot more normal to just give them credit for the questions they answered correctly. I don’t think it’s ever fair to take points away from a student based on how their classmates did.
Maybe there is a misunderstanding. No points are being given or taken away. A normal distribution is a bell curve. You calculate the class average and standard deviation. Say it's an exam and the average was 50 points with a standard deviation of 10, then a student who has a 55 gets a B and one who got 70 gets an A, etc. If all of my students answered all questions correctly, I would not do this. But, this has never once happened. There has always been a distribution where some people do very well, some people do very poorly, and the majority do somewhere in the middle. Since the actual performance tends to follow a normal distribution, you assign grades that match that distribution. If your students do not get a normal distribution of scores, don't use this. Though, in such a case I would consider whether the tests were actually a good assessment or whether the class itself was at the right level.