MOLB 7950 — Problem Sets
Problem Set Overview
Problem sets
We reinforce concepts with problem sets assigned at the end of each class. During the main blocks, problem sets on Mon and Wed should take ~60 minutes to complete. Problems sets assigned on Friday will be more substantial, requiring ~1-2 hours to complete. Together the problem sets constitute 60% of your grade.
Submission
Problem sets are distributed as Posit Cloud assignments. You will work on problem sets in an Rmarkdown document in the assignment. When complete, complete your assignment by submitting the URL from your Posit Cloud assignment into the assignment submission on Canvas. We will grade your problem directly in the Posit Cloud assignment.
Assigned | Due | Grades By | Who grades | Time to complete (approx) |
---|---|---|---|---|
Mon @ 12pm | Tues @ 5pm | Wed @ 5pm | Instructors / TAs | 60 min |
Tue @ 12pm | Wed @ 5pm | Thurs @ 5pm | Instructors / TAs | 60 min |
Wed @ 12pm | Thurs @ 5pm | Fri @ 5pm | Instructors / TAs | 60 min |
Thurs @ 12pm | Fri @ 5pm | Tues @ 5pm | Instructors / TAs | 60 min |
Fri @ 12pm | Mon @ 5pm | Wed @ 5pm | Instructors / TAs | 1-2 hr |
Problem Set Grading Rubric
Problem sets are worth 60% of your grade. Values in parentheses represent point values for each level from 20 points total. This rubric will be assessed at the end of the semester.
Criteria | Expert | Competent | Needs Improvement |
---|---|---|---|
Coding style | Student has gone beyond what was expected and required, coding manual is followed, code is well commented | Coding style lacks refinement and has some errors, but code is readable and has some comments | Many errors in coding style, little attention paid to making the code human readable |
Coding strategy | Complicated problem broken down into sub-problems that are individually much simpler. Code is efficient, correct, and minimal. Code uses appropriate data structure (list, data frame, vector/matrix/array). Code checks for common errors | Code is correct, but could be edited down to leaner code. Some “hacking” instead of using suitable data structure. Some checks for errors. | Code tackles complicated problem in one big chunk. Code is repetitive and could easily be functionalized. No anticipation of errors. |
Presentation: graphs | Graph(s) carefully tuned for desired purpose. One graph illustrates one point | Graph(s) well chosen, but with a few minor problems: inappropriate aspect ratios, poor labels. | Graph(s) poorly chosen to support questions. |
Presentation: tables | Table(s) carefully constructed to make it easy to perform important comparisons. Careful styling highlights important features. | Table(s) generally appropriate but possibly some minor formatting deficiencies. | Table(s) with too many, or inconsistent, decimal places. Table(s) not appropriate for questions and findings. Major display problems. |
Achievement, mastery, cleverness, creativity | Student has gone beyond what was expected and required, e.g., extraordinary effort, additional tools not addressed by this course, unusually sophisticated application of tools from course. | Tools and techniques from the course are applied very competently and, perhaps,somewhat creatively. Chosen task was acceptable, but fairly conservative in ambition. | Student does not display the expected level of mastery of the tools and techniques in this course. Chosen task was too limited in scope. |
Ease of access for instructor, compliance with course conventions for submitted work | Access as easy as possible, code runs! | Satisfactory | Not an earnest effort to reduce friction and comply with conventions and/or code does not run |