CS 473: Grading Policies

If you have any questions or concerns, please ask in lecture, during office hours, or on Piazza.


Graded work


Regrade requests


Final course grades

Final course grades will be determined as follows. (What do you expect from an algorithms course?)
  1. Compute raw totals from homework and exam scores.

     HwCount  = min(24, max(actual number of homework submissions, 16))
     HwAve    = (sum of HWcount highest homework scores) / (HWcount * 10) 
     ExAve    = (sum of exam scores) / (max possible sum of exam scores)
     HwWeight = HWcount * 0.0125
     ExWeight = 1.0 - HwWeight
     RawTotal = HwAve * HwWeight + ExAve * ExWeight
    

  2. Remove outliers and exceptional cases.
  3. Determine letter grades from total scores according to the following cutoffs. Each possible letter grade (except D+ and D–) covers a range of 6%. We reserve the right to lower these cutoffs.
  4. As a backup, determine letter grades using the actual distribution of total scores among undergraduates: For example, the B+/A– cutoff is 2/3 standard deviations above the mean, and the B–/C+ cutoff is 2/3 standard deviations below the mean. Outliers are excluded from the cutoff computation to avoid unfairly skewing the curve.
  5. Give each student the higher of the two letter grades. The fixed cutoffs were chosen to be slightly more generous than the curves in Jeff's previous offerings of 473 (see below), so we don't expect to apply the curve to anyone.

  6. Adjust grades upwards at the instructor's whim.

Past grade distributions

Here are the grade distributions for all Jeff's previous offerings of CS 473. This isn't really enough for the “typical” distribution to make sense, but there it is anyway. (Spring 2015 was a pilot offering, which did not use the current flexible homework percentage. Jeff also taught CS 473 in Spring 2020, but the course was graded on a strict Pass/No-Pass basis that semester.)

Semester Mean ± stdev Min pass #As #Bs #Cs #Ds #Fs
Spring 2015* 65% ± 12% 42% ugrads: 7 12 5 0 0
grads: 13 6 0 0 0
Spring 2016 74% ± 11% 42% ugrads: 27 29 21 3 0
grads: 11 11 0 0 0
Spring 2017 73% ± 13% 41% ugrads: 28 30 22 3 4
grads: 6 7 3 0 0
Typical 72% ± 12% 42% ugrads: 32% 37% 25% 3% 2%
grads: 52% 42% 5% 0% 0%

You can compare my grade distributions with others' here.