CS/ECE 374 A: Grading Policies

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


Graded work


Regrade requests

If you believe that your score for any homework or exam problem is inconsistent with the published grading rubric, or that you were graded more harshly than other students, you can request a regrade.

Overall course grades

Unlike previous offerings of this course, which were graded strictly on a curve, this semester we will be using both absolute letter grade cutoffs and a curve. We will compute letter grades for all students using both methods; each student will receive the higher of the two computed letter grades.

We will determine final course grades as follows. (What do you expect from an algorithms course?)

  1. Compute raw totals from homework and exam scores, excluding extra credit.
     HwCount  = min(25, max(actual number of homework submissions, 15))
     HwAve    = (sum of HwCount highest homework scores) / (HwCount * 10) 
     HwWeight = HwCount * 0.014
     
     ExAve    = (sum of exam scores) / (max possible sum of exam scores)
     ExWeight = 1.0 - HWweight 
     RawTotal = HwAve * HwWeight + ExAve * ExWeight
    

  2. Compute adjusted totals by adding extra credit points to raw totals. Extra credit points are not necessarily worth the same as regular points.

  3. Identify outliers and exceptional cases.

  4. Determine fixed letter grades from adjusted totals, according to the following cutoffs. Each possible letter grade above F covers an interval of length 5%. We reserve the right to lower the cutoffs.

  5. Determine curved letter-grade cutoffs from the distribution of raw totals. To avoid skewing the curve, outliers are excluded from this cutoff computation, as are students with forgiven exams, a signifcant number of forgiven homework, or zeros from cheating offenses. For example, the B+/B cutoff is 2/3 standard deviations above the mean, and the D/D– cutoff is 5/3 standard deviations below the mean. The fixed cutoffs are consistent with a mean of 70% and a standard deviation of 15%.

  6. Compute curved letter grades (for non-outliers) from adjusted totals.

  7. Your actual letter grade is either your fixed leter grade or your curved letter grade, whichever is higher. If the curve would help your grade, we will let it. If the curve would hurt your grade, we will ignore it. There is no budget of As or A+s.

Past grade distributions

Here are the grade distributions for all of Jeff's previous offerings of CS 374. Like this semester, the mean was set at the C+/B– boundary, and each standard deviation was worth a full letter grade. Spring 2014 and Fall 2014 were pilot offerings, with significantly smaller enrollments, unsettled curricula, and no flexible homework percentage. I do not understand the jump in average scores between Fall 2016 and Spring 2018. Guided Problem Sets and fixed grade cutoffs were introduced in Fall 2021, along with lower weights for exams.

Semester Mean ± stdev Min pass #As #Bs #Cs #Ds #Fs
Spring 2014 59% ± 11% 38% 8 11 8 8 1
Fall 2014 62% ± 12% 38% 16 22 22 12 0
Fall 2016 64% ± 12% 39% 87 113 124 60 14
Spring 2018 71% ± 13% 44% 70 87 74 36 5
Fall 2019 71% ± 12% 47% 68 101 89 54 8

Historically, students' grades in this course are almost entirely determined by their exam scores. In a typical semester:

The following scatterplot shows the distribution of homework averages versus exam scores for Fall 2019. Notice especially the outliers: One student had a homework average below 70% but an exam average above 90%; several students had homework average over 90% but exam averages below 40%.